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  1. Malik AA, Rajandram R, Tah PC, Hakumat-Rai VR, Chin KF
    J Crit Care, 2016 Apr;32:182-8.
    PMID: 26777745 DOI: 10.1016/j.jcrc.2015.12.008
    Gut failure is a common condition in critically ill patients in the intensive care unit (ICU). Enteral feeding is usually the first line of choice for nutrition support in critically ill patients. However, enteral feeding has its own set of complications such as alterations in gut transit time and composition of gut eco-culture. The primary aim of this study was to investigate the effect of microbial cell preparation on the return of gut function, white blood cell count, C-reactive protein levels, number of days on mechanical ventilation, and length of stay in ICU. A consecutive cohort of 60 patients admitted to the ICU in University Malaya Medical Centre requiring enteral feeding were prospectively randomized to receive either treatment (n = 30) or placebo (n = 30). Patients receiving enteral feeding supplemented with a course of treatment achieved a faster return of gut function and required shorter duration of mechanical ventilation and shorter length of stay in the ICU. However, inflammatory markers did not show any significant change in the pretreatment and posttreatment groups. Overall, it can be concluded that microbial cell preparation enhances gut function and the overall clinical outcome of critically ill patients receiving enteral feeding in the ICU.
  2. Chew SC, Beh ZY, Hakumat Rai VR, Jamaluddin MF, Ng CC, Chinna K, et al.
    J Vasc Access, 2020 Jan;21(1):26-32.
    PMID: 31148509 DOI: 10.1177/1129729819852057
    PURPOSE: Central venous catheter insertion is a common procedure in the intensive care setting. However, complications persist despite real-time ultrasound guidance. Recent innovation in needle navigation technology using guided positioning system enables the clinician to visualize the needle's real-time position and trajectory as it approaches the target. We hypothesized that the guided positioning system would improve performance time in central venous catheter insertion.

    METHODS: A prospective randomized study was conducted in a single-center adult intensive care unit. In total, 100 patients were randomized into two groups. These patients underwent internal jugular vein central venous catheter cannulation with ultrasound guidance (short-axis scan, out-of-plane needling approach) in which one group adopted conventional method, while the other group was aided with the guided positioning system. Outcomes were measured by procedural efficacy (success rate, number of attempts, time to successful cannulation), complications, level of operators' experience, and their satisfaction.

    RESULTS: All patients had successful cannulation on the first attempt except for one case in the conventional group. The median performance time for the guided positioning system method was longer (25.5 vs 15.5 s; p = 0.01). And 86% of the operators had more than 3-year experience in anesthesia. One post-insertion hematoma occurred in the conventional group. Only 88% of the operators using the guided positioning system method were satisfied compared to 100% in the conventional group.

    CONCLUSION: Ultrasound-guided central venous catheter insertion via internal jugular vein was a safe procedure in both conventional and guided positioning system methods. The guided positioning system did not confer additional benefit but was associated with slower performance time and lower satisfaction level among the experienced operators.

  3. Tah PC, Lee ZY, Poh BK, Abdul Majid H, Hakumat-Rai VR, Mat Nor MB, et al.
    Crit Care Med, 2021 08 01;49(8):e804-e805.
    PMID: 34261937 DOI: 10.1097/CCM.0000000000005082
  4. Tah PC, Lee ZY, Poh BK, Abdul Majid H, Hakumat-Rai VR, Mat Nor MB, et al.
    Crit Care Med, 2020 05;48(5):e380-e390.
    PMID: 32168031 DOI: 10.1097/CCM.0000000000004282
    OBJECTIVES: Several predictive equations have been developed for estimation of resting energy expenditure, but no study has been done to compare predictive equations against indirect calorimetry among critically ill patients at different phases of critical illness. This study aimed to determine the degree of agreement and accuracy of predictive equations among ICU patients during acute phase (≤ 5 d), late phase (6-10 d), and chronic phase (≥ 11 d).

    DESIGN: This was a single-center prospective observational study that compared resting energy expenditure estimated by 15 commonly used predictive equations against resting energy expenditure measured by indirect calorimetry at different phases. Degree of agreement between resting energy expenditure calculated by predictive equations and resting energy expenditure measured by indirect calorimetry was analyzed using intraclass correlation coefficient and Bland-Altman analyses. Resting energy expenditure values calculated from predictive equations differing by ± 10% from resting energy expenditure measured by indirect calorimetry was used to assess accuracy. A score ranking method was developed to determine the best predictive equations.

    SETTING: General Intensive Care Unit, University of Malaya Medical Centre.

    PATIENTS: Mechanically ventilated critically ill patients.

    INTERVENTIONS: None.

    MEASUREMENTS AND MAIN RESULTS: Indirect calorimetry was measured thrice during acute, late, and chronic phases among 305, 180, and 91 ICU patients, respectively. There were significant differences (F= 3.447; p = 0.034) in mean resting energy expenditure measured by indirect calorimetry among the three phases. Pairwise comparison showed mean resting energy expenditure measured by indirect calorimetry in late phase (1,878 ± 517 kcal) was significantly higher than during acute phase (1,765 ± 456 kcal) (p = 0.037). The predictive equations with the best agreement and accuracy for acute phase was Swinamer (1990), for late phase was Brandi (1999) and Swinamer (1990), and for chronic phase was Swinamer (1990). None of the resting energy expenditure calculated from predictive equations showed very good agreement or accuracy.

    CONCLUSIONS: Predictive equations tend to either over- or underestimate resting energy expenditure at different phases. Predictive equations with "dynamic" variables and respiratory data had better agreement with resting energy expenditure measured by indirect calorimetry compared with predictive equations developed for healthy adults or predictive equations based on "static" variables. Although none of the resting energy expenditure calculated from predictive equations had very good agreement, Swinamer (1990) appears to provide relatively good agreement across three phases and could be used to predict resting energy expenditure when indirect calorimetry is not available.

  5. Tah PC, Poh BK, Kee CC, Lee ZY, Hakumat-Rai VR, Mat Nor MB, et al.
    Eur J Clin Nutr, 2022 Apr;76(4):527-534.
    PMID: 34462560 DOI: 10.1038/s41430-021-00999-y
    BACKGROUND: Predictive equations (PEs) for estimating resting energy expenditure (REE) that have been developed from acute phase data may not be applicable in the late phase and vice versa. This study aimed to assess whether separate PEs are needed for acute and late phases of critical illness and to develop and validate PE(s) based on the results of this assessment.

    METHODS: Using indirect calorimetry, REE was measured at acute (≤5 days; n = 294) and late (≥6 days; n = 180) phases of intensive care unit admission. PEs were developed by multiple linear regression. A multi-fold cross-validation approach was used to validate the PEs. The best PEs were selected based on the highest coefficient of determination (R2), the lowest root mean square error (RMSE) and the lowest standard error of estimate (SEE). Two PEs developed from paired 168-patient data were compared with measured REE using mean absolute percentage difference.

    RESULTS: Mean absolute percentage difference between predicted and measured REE was <20%, which is not clinically significant. Thus, a single PE was developed and validated from data of the larger sample size measured in the acute phase. The best PE for REE (kcal/day) was 891.6(Height) + 9.0(Weight) + 39.7(Minute Ventilation)-5.6(Age) - 354, with R2 = 0.442, RMSE = 348.3, SEE = 325.6 and mean absolute percentage difference with measured REE was: 15.1 ± 14.2% [acute], 15.0 ± 13.1% [late].

    CONCLUSIONS: Separate PEs for acute and late phases may not be necessary. Thus, we have developed and validated a PE from acute phase data and demonstrated that it can provide optimal estimates of REE for patients in both acute and late phases.

    TRIAL REGISTRATION: ClinicalTrials.gov NCT03319329.

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